Computing movement speed

MovingPandas offers functions to compute and/or visualize the speed of movement along the trajectory between consecutive points.

import pandas as pd
import geopandas as gpd
import movingpandas as mpd
import shapely as shp
import hvplot.pandas 

from geopandas import GeoDataFrame, read_file
from shapely.geometry import Point, LineString, Polygon
from datetime import datetime, timedelta
from holoviews import opts

import warnings
warnings.filterwarnings('ignore')

opts.defaults(opts.Overlay(active_tools=['wheel_zoom'], frame_width=500, frame_height=400))

mpd.show_versions()

MovingPandas 0.11.rc1

SYSTEM INFO
-----------
python     : 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:50:36) [MSC v.1929 64 bit (AMD64)]
executable : H:\miniconda3\envs\movingpandas\python.exe
machine    : Windows-10-10.0.19043-SP0

GEOS, GDAL, PROJ INFO
---------------------
GEOS       : None
GEOS lib   : None
GDAL       : 3.5.0
GDAL data dir: None
PROJ       : 9.0.0
PROJ data dir: H:\miniconda3\pkgs\proj-9.0.0-h1cfcee9_1\Library\share\proj

PYTHON DEPENDENCIES
-------------------
geopandas  : 0.11.1
pandas     : 1.4.3
fiona      : 1.8.21
numpy      : 1.23.1
shapely    : 1.8.2
rtree      : 1.0.0
pyproj     : 3.3.0
matplotlib : 3.5.2
mapclassify: 2.4.3
geopy      : 2.2.0
holoviews  : 1.14.8
hvplot     : 0.8.0
geoviews   : 1.9.5
stonesoup  : 0.1b9

Basic example

df = pd.DataFrame([
  {'geometry':Point(0,0), 't':datetime(2018,1,1,12,0,0)},
  {'geometry':Point(6,0), 't':datetime(2018,1,1,12,0,6)},
  {'geometry':Point(6,6), 't':datetime(2018,1,1,12,0,11)},
  {'geometry':Point(9,9), 't':datetime(2018,1,1,12,0,14)}
]).set_index('t')
gdf = GeoDataFrame(df, crs=31256)
toy_traj = mpd.Trajectory(gdf, 1)
toy_traj

Trajectory 1 (2018-01-01 12:00:00 to 2018-01-01 12:00:14) | Size: 4 | Length: 16.2m
Bounds: (0.0, 0.0, 9.0, 9.0)
LINESTRING (0 0, 6 0, 6 6, 9 9)

toy_traj.add_speed(overwrite=True)
toy_traj.df

	geometry	speed
t
2018-01-01 12:00:00	POINT (0.000 0.000)	1.000000
2018-01-01 12:00:06	POINT (6.000 0.000)	1.000000
2018-01-01 12:00:11	POINT (6.000 6.000)	1.200000
2018-01-01 12:00:14	POINT (9.000 9.000)	1.414214

We can also visualize the speed values:

toy_traj.plot(column="speed", linewidth=5, capstyle='round', legend=True)

<AxesSubplot:>

Similar to speed, we can also add other columns:

toy_traj.add_direction(overwrite=True)
toy_traj.df

	geometry	speed	direction
t
2018-01-01 12:00:00	POINT (0.000 0.000)	1.000000	90.0
2018-01-01 12:00:06	POINT (6.000 0.000)	1.000000	90.0
2018-01-01 12:00:11	POINT (6.000 6.000)	1.200000	0.0
2018-01-01 12:00:14	POINT (9.000 9.000)	1.414214	45.0

toy_traj.add_timedelta(overwrite=True)
toy_traj.df

	geometry	speed	direction	timedelta
t
2018-01-01 12:00:00	POINT (0.000 0.000)	1.000000	90.0	NaT
2018-01-01 12:00:06	POINT (6.000 0.000)	1.000000	90.0	0 days 00:00:06
2018-01-01 12:00:11	POINT (6.000 6.000)	1.200000	0.0	0 days 00:00:05
2018-01-01 12:00:14	POINT (9.000 9.000)	1.414214	45.0	0 days 00:00:03

Real-world trajectories

gdf = read_file('../data/geolife_small.gpkg')
traj_collection = mpd.TrajectoryCollection(gdf, 'trajectory_id', t='t')

my_traj = traj_collection.trajectories[1]

my_traj.df

	id	sequence	trajectory_id	tracker	geometry
t
2009-06-29 07:02:25	1556	1090	2	0	POINT (116.59096 40.07196)
2009-06-29 07:02:30	1557	1091	2	0	POINT (116.59091 40.07201)
2009-06-29 07:02:35	1558	1092	2	0	POINT (116.59088 40.07203)
2009-06-29 07:02:40	1559	1093	2	0	POINT (116.59091 40.07200)
2009-06-29 07:02:45	1560	1094	2	0	POINT (116.59096 40.07198)
...	...	...	...	...	...
2009-06-29 11:09:47	2448	1982	2	0	POINT (116.32349 40.00037)
2009-06-29 11:09:57	2449	1983	2	0	POINT (116.32513 40.00057)
2009-06-29 11:10:02	2450	1984	2	0	POINT (116.32688 40.00087)
2009-06-29 11:10:07	2451	1985	2	0	POINT (116.32722 40.00101)
2009-06-29 11:13:12	2452	1986	2	0	POINT (116.32746 40.00052)

897 rows × 5 columns

Even if the GeoDataFrame does not contain a speed column, we can still plot movement speed:

my_traj.plot(column='speed', linewidth=5, capstyle='round', figsize=(9,3), legend=True, vmax=20)

<AxesSubplot:>

my_traj.hvplot(c='speed', clim=(0,20), line_width=7.0, tiles='CartoLight', cmap='Viridis', colorbar=True)

traj_collection.plot(column='speed', linewidth=5, capstyle='round', legend=True, vmax=20)